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Test For Newer Python Versions #849

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Test For Newer Python Versions #849

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9d12f03
new pythons
ksolarski Feb 20, 2024
f11d0a2
new checkout
ksolarski Feb 20, 2024
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6 changes: 3 additions & 3 deletions .github/workflows/build.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -10,12 +10,12 @@ jobs:
# You can use PyPy versions in python-version.
# For example, pypy2 and pypy3
matrix:
python-version: [3.9]
python-version: ["3.9", "3.10", "3.11", "3.12"]

steps:
- uses: actions/checkout@v2
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
# You can test your matrix by printing the current Python version
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7 changes: 3 additions & 4 deletions orbit/template/dlt.py
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Original file line number Diff line number Diff line change
Expand Up @@ -751,10 +751,9 @@ def predict(
global_trend_level + global_trend_slope * idx * self._time_delta
)
elif self.global_trend_option == GlobalTrendOption.loglinear.name:
full_global_trend[
:, idx
] = global_trend_level + global_trend_slope * np.log(
1 + idx * self._time_delta
full_global_trend[:, idx] = (
global_trend_level
+ global_trend_slope * np.log(1 + idx * self._time_delta)
)
elif self.global_trend_option == GlobalTrendOption.logistic.name:
full_global_trend[:, idx] = self.global_floor + (
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12 changes: 6 additions & 6 deletions orbit/template/ktrlite.py
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Original file line number Diff line number Diff line change
Expand Up @@ -190,9 +190,9 @@ def set_init_values(self):
init_values = None
if len(self._seasonality) > 1 and self.num_of_regressors > 0:
init_values = dict()
init_values[
RegressionSamplingParameters.COEFFICIENTS_KNOT.value
] = np.zeros((self.num_of_regressors, self.num_knots_coefficients))
init_values[RegressionSamplingParameters.COEFFICIENTS_KNOT.value] = (
np.zeros((self.num_of_regressors, self.num_knots_coefficients))
)
self._init_values = init_values

def _set_default_args(self):
Expand Down Expand Up @@ -497,9 +497,9 @@ def predict(
seas_regression = np.sum(
seas_coef * seasonal_regressor_matrix.transpose(1, 0), axis=-2
)
seas_decomp[
"seasonality_{}".format(self._seasonality[idx])
] = seas_regression
seas_decomp["seasonality_{}".format(self._seasonality[idx])] = (
seas_regression
)
pos += len(cols)
total_seas_regression += seas_regression
if include_error:
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6 changes: 3 additions & 3 deletions orbit/template/lgt.py
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Original file line number Diff line number Diff line change
Expand Up @@ -231,9 +231,9 @@ def set_init_values(self):
-1.0,
1.0,
)
init_values[
LatentSamplingParameters.INITIAL_SEASONALITY.value
] = init_sea
init_values[LatentSamplingParameters.INITIAL_SEASONALITY.value] = (
init_sea
)
if self.num_of_positive_regressors > 0:
x = np.clip(
np.random.normal(
Expand Down